diffLine-based diff of two texts. Returns unified diff plus structured changes (added/removed/unchanged counts and hunks). POST { a, b, context? } (max 200KB each). Price: $0.002/call with credits key; free demo without (2KB input cap).
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | ||
| b | Yes | ||
| context | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral transparency burden. It discloses that the diff is line-based, the output includes unified diff and structured changes, and there are size and pricing limits. No contradiction with annotations exists since there are none.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using three sentences to cover purpose, output, request format, limits, and pricing. Every clause contributes meaningful information with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple diff tool with no output schema, the description covers the essential aspects: what it does, what it returns, how to call it, and constraints. It is nearly complete, but the unexplained context parameter leaves a minor gap in off-the-shelf usability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameter semantics. It names a, b, and context?, and 'two texts' implies a and b are strings, but it never explains what context means, its default, or its effect. This is a clear gap for such a minimal parameter set.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with 'Line-based diff of two texts,' which clearly states the verb and resource. It additionally describes the return format, making it unmistakable what the tool does and distinguishing it from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for use: comparing two texts line-by-line, and includes practical constraints (max 200KB each, demo cap). It does not explicitly mention alternatives or exclusions, but the sibling tools are unrelated, so this is not a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a unique, non-overlapping purpose. Even closely related tools like html_to_markdown and markdown_to_html are clearly inverses, and read_page combines fetching and conversion, so no two tools could be confused for the same task.
All names are lowercase with underscores, maintaining a consistent syntactic style. However, there is no strict verb-noun pattern: some names are nouns (cron, diff, qr, timezone), others are verbs (convert, extract), and word order varies (email_verify vs validate_ids), which is a minor deviation.
With 13 tools, the count is well within the ideal 3-15 range. Each tool provides a distinct paid utility, and none feel redundant or out of place for a general-purpose vending machine API.
The tool surface covers a broad range of common utilities—format conversion, validation, extraction, formatting, and time handling. There are minor gaps like missing YAML conversion or raw HTML fetching, but these are not critical for the server's stated purpose as a collection of paid utilities.